code: def test_uu_predict_too_few_blended():
      algo = knn.UserUser(30, min_nbrs=2)
      algo.fit(ml_ratings)
  
      preds = algo.predict_for_user(4, [1016, 2091])
      assert len(preds) == 2
      assert np.isnan(preds.loc[2091])
      assert preds.loc[1016] == approx(3.62221550680778)
  
imports: from lenskit.algorithms import Recommender
  import lenskit.algorithms.user_knn
  from lenskit.util import clone
  from pathlib import Path
  import logging
  import pickle
  import pandas
  import numpy
  from scipy.sparse import linalg
  from pytest import approx, mark
  import lenskit.util.test
label_desc: Use image node_id 9 for calling a global function with example usage: test_uu_predict_too_few_blended() without return types